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Truss Decomposition in Massive Networks
The k-truss is a type of cohesive subgraphs proposed recently for the study of networks. While the problem of computing most cohesive subgraphs is NP-hard, there exists a polynomial time algorithmExpand
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Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs
The rapid growth in the volume of many real-world graphs (e.g., social networks, web graphs, and spatial networks) has led to the development of various vertex-centric distributed graph computingExpand
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A model-based approach to attributed graph clustering
Graph clustering, also known as community detection, is a long-standing problem in data mining. However, with the proliferation of rich attribute information available for objects in real-worldExpand
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TF-Label: a topological-folding labeling scheme for reachability querying in a large graph
Reachability querying is a basic graph operation with numerous important applications in databases, network analysis, computational biology, software engineering, etc. Although many indexes have beenExpand
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Path Problems in Temporal Graphs
Shortest path is a fundamental graph problem with numerous applications. However, the concept of classic shortest path is insufficient or even flawed in a temporal graph, as the temporal informationExpand
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Effective Techniques for Message Reduction and Load Balancing in Distributed Graph Computation
Massive graphs, such as online social networks and communication networks, have become common today. To efficiently analyze such large graphs, many distributed graph computing systems have beenExpand
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Efficient core decomposition in massive networks
The k-core of a graph is the largest subgraph in which every vertex is connected to at least k other vertices within the subgraph. Core decomposition finds the k-core of the graph for every possibleExpand
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Triangle listing in massive networks and its applications
Triangle listing is one of the fundamental algorithmic problems whose solution has numerous applications especially in the analysis of complex networks, such as the computation of clusteringExpand
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Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks
We study the problem of point-to-point distance querying for massive scale-free graphs, which is important for numerous applications. Given a directed or undirected graph, we propose to build anExpand
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Bilinear Factor Matrix Norm Minimization for Robust PCA: Algorithms and Applications
The heavy-tailed distributions of corrupted outliers and singular values of all channels in low-level vision have proven effective priors for many applications such as background modeling,Expand
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